Journal of Shanghai Jiao Tong University ›› 2024, Vol. 58 ›› Issue (2): 232-241.doi: 10.16183/j.cnki.jsjtu.2022.322

• Naval Architecture, Ocean and Civil Engineering • Previous Articles     Next Articles

In-Situ X-Ray CT Characterization of Damage Mechanism of Plain Weave SiCf/SiC Composites Under Compression

CHENG Xiangwei1, ZHANG Daxu1(), DU Yonglong1, GUO Hongbao2, HONG Zhiliang2   

  1. 1. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    2. Aero Engine Corporation of China Commercial Aircraft Engine Co., Ltd., Shanghai 201180, China
  • Received:2022-08-24 Revised:2022-10-10 Accepted:2022-10-18 Online:2024-02-28 Published:2024-03-04

Abstract:

In order to reveal the damage evolution and failure mechanism of ceramic matrix composites (CMCs), in-situ X-ray CT compression tests of plain weave SiCf/SiC composites were conducted, and the CT data during loading and after failure were obtained. Displacement and strain distributions of the material were evaluated by the digital volume correlation (DVC) technology. The three-dimensional visual model of the composite was created by using image processing software. The spatial distributions of tow split and other damages were segmented by the deep learning algorithm. The qualitative and quantitative analysis of compression damage evolution were performed. The results show that there is a relatively large expansion induced by barreling in the thickness direction and a little shrinkage in the width direction during the unidirectional compression, while the barreling in the thickness direction is the main reason to trigger compressive damages of the material. Damages such as matrix falling-off at surface, tow split, delamination, will occur as the compression was approaching the ultimate load. Fiber kinking results in the final compressive failure of the material, while an obvious V-shaped shear band is observed in the fracture. The analysis of compressive damage evolution of plain weave SiCf/SiC shows that the DVC technology and deep learning-based image segmentation methods could effectively reveal the compressive damage evolution mechanism of ceramic matrix composites.

Key words: ceramic matrix composites (CMCs), silicon carbide, deep learning, image segmentation, digital volume correlation (DVC) technology

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